INVESTMENT AND PRODUCTIVITY IN THE AGRO-INDUSTRIAL SECTOR: A CASE STUDY

The productivity of a sector, an important determinant of competitiveness, depends, among other factors, on the investment made. In this context, the main aim of this work is to explore the relation between investment and productivity trends, based on the amounts of investment made in the agri-food industry in Northern Portugal (NUT II), as well as the asymmetries at sub-regional level, during the last two EU support frameworks, namely QREN (2007-13) and Portugal 2020 (2014-2020). This study will start by gathering information from organizations that manage EU funds related to the beverage and food industries. This data will be categorized by subsectors and regions to estimate access. The research will then analyse productivity trends in these sectors and the impact of investment on productivity using statistical analysis techniques. The results show that there is a positive and significant relation between gross fixed capital formation and the productivity of both industries: food and beverage. In what refers, specifically to the beverage industry, we obtain significant results in the elasticity model. The findings show that it possible to gauge the effectiveness of policies to support investment, namely by identifying the most dynamic sectors in terms of attracting funds and with the greatest impact in terms of productivity, i.e. assessing the return on investment that is essentially private and supported with public funds, as well as identifying strategic sectors and promoting transparency and accountability in the management of public resources.

Teresa SEQUEIRA - Assistant Professor, University of Trás-os-Montes and Alto Douro, Portugal. Researcher at the Centre for Transdisciplinary Development Studies (CETRAD). E-mail: tsequeir@utad.pt (corresponding author)

Conceicao REGO - Assistant Professor, University of Évora, Portugal. Researcher at the Center for Advanced Studies in Management and Economics (CEFAGE). E-mail: mcpr@uevora.pt

Andreia DIONISIO - Associate Professor with Aggregation, University of Évora, Portugal. Researcher at the Center for Advanced Studies in Management and Economics (CEFAGE). E-mail: andreia@uevora.pt

R12, R58

A COMBINED GRAPH THEORETIC AND TRANSPORT PLANNING FRAMEWORK FOR THE ECONOMIC AND FUNCTIONAL ANALYSIS OF LARGE-SCALE ROAD NETWORKS

Road networks are the backbone of our society and a built capital enabling the movement of people and transportation of goods. Their design should comply with both traffic and technical requirements and economic demand, to ensure efficient connectivity, accessibility, optimum resource allocation, and long- term sustainability. Poised on the intersection of this bi-dimensional context, this paper develops a methodological framework incorporating these two dimensions in road network analysis to evaluate both functional and economic aspects of the network. Within this framework, we incorporate functional and economic information into an interurban road graph model constructed on empirical data from Greece, and we afterward evaluate the level of determination and the model’s applicability and usefulness in transportation planning. Overall, our findings reveal the proposed approach capable of evaluating potential interventions in the network and estimating traffic volumes, especially in data- constrained situations. In empirical terms, they indicate that the socio-economic performance of the national road network is satisfactory, albeit not fully optimized.

Maria STAVARA - Researcher, Department of Planning and Regional Development, University of Thessaly, Volos, Greece mstavara@uth.gr

Dimitrios TSIOTAS - Assistant Professor, Department of Regional and Economic Development, School of Applied Economics and Social Sciences, Agricultural University of Athens, Amfissa, Greece tsiotas@aua.gr (Corresponding Author)

R41, R42

SMART CITY INITIATIVES AND ECONOMIC GROWTH IN INDIA: AN EMPIRICAL ANALYSIS

In developing countries, cities are vying with each other to improve their infrastructure to attract business activities and become more efficient, effective, and sustainable. Against this backdrop, the 'Smart City Mission' is one of the flagship Indian government initiatives started in 2015. In order to provide people with a high-quality living, smart cities are the latest urban conceptions. It is the idea of combining different technologies to create sustainable and intelligent practices. However, the quantitative assessment of this initiative on urbanization in India is very limited. In this study, we assess the impact of smart city projects on urbanization, which is measured by city population size and city gross domestic product. The results show that the mission has a mixed effect on urbanization. Though it increases the size of the city's population, it does not promote city income. Therefore, implementing a smart city mission has to be done in the hinterland area along with the core area of a city. Finally, it discusses the challenges faced and their potential solutions. The results suggest several policies for making urbanization a success and making India a developed country.

Arshima KHAN - Symbiosis School of Economics, SB Road, Pune – 411004, Email: arshima.khan.2022@sse.ac.in

Sabyasachi TRIPATHI - Associate Professor, Symbiosis School of Economics, SB Road, Pune – 411004, Email: sabyasachi.tripathi@sse.ac.in

Jyoti CHANDIRAMANI - Professor and Director, Symbiosis School of Economics, SB Road, Pune – 411004, Email: jyoti.chandiramani@sse.ac.in

C10, I31, R11

THE EFFICACY OF TECHNICAL ANALYSIS IN THE FOREIGN EXCHANGE MARKET: A CASE STUDY OF THE USD/JPY PAIR

Financial markets, known for their unpredictability (Lee, 2020), present significant challenges for researchers. Technical analysis, rooted in the principle of market efficiency, focuses on price movements to predict future trends (Fang & Jacobsen, 2024). Originating in the 17th century, technical analysis has gained prominence in modern financial markets (Dongrey, 2022). Technical analysts rely on historical forex data (Garza Sepúlveda et al., 2023) and employ various tools, including candlestick patterns, moving averages, trendlines, resistance levels, and indicators like Bollinger Bands, MACD, RSI, and moving averages, to forecast price movements (Oktaba & Grzywińska-Rąpca, 2024). This study aimed to evaluate the effectiveness of technical analysis in the foreign exchange market by analyzing historical USD/JPY data from 2019, a period unaffected by major global events. The USD/JPY pair was chosen due to its high volatility and economic significance (Fiszeder, 2018 and Peng et al., 2021). Our analysis involved identifying support and resistance levels, trends, and applying various technical indicators to assess their effectiveness in predicting market movements (Mate & Jimeńez, 2021). The findings validate the use of technical analysis tools, demonstrating their ability to identify potential reversal and continuation zones.

Fernando TEIXEIRA - Professor Assistant, Instituto Politécnico de Beja, Portugal Smart Cities Research Center fernando.teixeira@ipbeja.pt

Susana Soares Pinheiro Vieira PESCADA - Professor Assistant, Faculty of Economy, University of Algarve, Portugal Cin Turs - Research Center for Tourism, Sustainability and Well-being spescada@ualg.pt

Filipos RUXHO - Professor Assistant, Faculty of Agribusiness, University Haxhi Zeka of Preja, Kosovo Filipos.ruxho@unhz.eu

G10, G14, G15